You Have the Data, Now What?

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1 You Have the Data, Now What? Using the AVL Data to Improve On-Time Performance on Commuter Express Lines Joseph Raquel, Planning Director TransTrack User Group October 15, 2013

2 Foothill Transit Region 327 Square Miles San Gabriel Valley Pomona Valley Downtown Los Angeles 33 fixed-route lines

3 Agency Statistics Fleet 300 Vehicles Service Hours 690,000/year Service Miles ~12M /year Passenger Boardings ~15,000,000/year FY 2014 Budget Operations $75M Capital $34M Total $109M

4 Agency Structure Unique Public/Private Partnership Public: Joint Powers Authority and Administration Administration Staff 22 member-cities Los Angeles County Representatives from each Private: Contracted Operations Pomona Operation Facility First Transit Arcadia Operations Facility First Transit Transit Stores and Facility/ Bus Stop- Veolia Transportation Executive Board

5 Foothill Transit s Mission Statement To be the premier public transit provider committed to: Safety Courtesy Quality Responsiveness Efficiency Innovation

6 Goals and Performance Indicators Operate a Safe Transit System Goals Provide Outstandin g Customer Service Operate an Effective Transit System Operate an Efficient Transit System 6

7 Key Performance Indicator Preventable Accidents Complaints Schedule Adherence Miles Between Service Interruptions Average Hold Times Boardings per Vehicle Service Hour Average Weekday Boardings Cost per Vehicle Service Hour Farebox Recovery Ratio

8 KPI Summary FY 14 Performance Indicator Target Preventable Accidents per 100,000 miles.60 Complaints per 100,000 Miles Schedule Adherence 90% Average Hold Time :45 Miles Between Service Interruptions 15,000 Boardings per Vehicle Service Hours 19.1* Average Weekday Boardings 49,250* Average Cost per Hour Vehicle Service Hour $98.59* Farebox Recovery Ratio 25.83%* * FY14 Target changed

9 Beyond Dashboards Clipboards to Computers Flipping the Switch Using AVL Data to report statistics

10 Where s the data coming from?

11 Taming the data

12 How close are we? (Then) On time performance improvement Initial 44% to as high as 74% Moving towards new way to monitor service Starting to trust the data

13 Foothill Transit Now New way to monitor the system Better understanding of the AVL system Pains of Radio Data Channel vs. Cellular Importance of Maintenance Importance of Driver Log In Clean Schedule Import Using the data to improve system performance

14 Joe Planner Transition from IT to Planning Understand how the data is produced Analyze the data Producer to Consumer

15 Improve Schedule Adherence on Commuter Express Routes 6 Routes 5 into Downtown LA 1 into Pasadena Operates only during AM/PM Peak, one way 15% of overall riders 3% Impact on System OTP Free Running Time

16 Line 493 Schedule

17 OTP Express Routes FY13 Q Overall 2012 West 2012 East July 59% 87% 40% August 51% 87% 43% Sept 63% 87% 47%

18 Data Tells a Story

19 Field Observations 3 Evenings Team of 5 Stationed at each timepoint Recorded Bus Number and Departure Time Special Events Clipper Game

20 AVL Data Data was already in the system More efficient Lots of data available

21 Looking at the Data Issues with AVL Data May not be complete Incomplete Trips/ Missing Timepoints Uncorrelated- System does not know which route to place data Attempt to correlate data TransTrack Algorithm to place stops via GPS data, Block ID, and vehicle s prior stops

22 AVL View

23 Analyzing The Data 1 Years Worth of Data by Route Imported the data into Excel Sorting, Date/Bus/Block/Scheduled Departure Time difference from one timepoint to another (Travel Time) Average Travel Time

24 The Art of Analyzing Data Look closely at the data Outliers Negative Numbers Unrealistic Travel Times Analysis by time of day Analysis by day (non-commuter routes)

25 Run Time Data Compared the Actual Run Time vs. Scheduled Compared the system data to observed data Look at the Schedule Adherence Dashboard Plot the data Built into some scheduling software No Correlation function As good as your AVL data

26 Run Time Data Comparison

27 Plugged the Data into Hastus Wait for the schedule change to occur Wait for the data to accumulate

28 OTP Express Routes FY13 Q Overall 2012 West 2012 East July 59% 87% 40% August 51% 87% 43% Sept 63% 87% 47%

29 The Results 2013 Overall 2013 West 2013 East July 83% 90% 79% August 76% 88% 70% Sept 80% 89% 75%

30 Comparison 2012 Overall 2012 West 2012 East July 59% 87% 40% August 51% 87% 43% Sept 63% 87% 47% 2013 Overall 2013 West 2013 East July 83% 90% 79% August 76% 88% 70% Sept 80% 89% 75%

31 Lessons Learned Analyze, analyze, analyze Importance of keeping the AVL maintained Field observations are valuable Data tells a story

32 Going Forward Analyze the local lines November Schedule Change On going analysis of run times Looking at incorporating cellular data communication TransTrack create the run time report

33 Questions Joseph Raquel, Planning Director

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